Wikis, surveys, and webwhompers

Continuing on the thread of when have I seen wikis work the best... In my last post I answered that I have seen wikis work quite well when they are tightly controlled. I described the LeaderNetwork wiki, which only allows editing by Claire Reinelt and me.

Another good way of controlling a wiki is not by limiting the number of editors (as in the previous example) but by limiting the contributions asked of each editor.

Used in this way, a wiki is quite similar to an online survey. The wiki begins with a clear list of questions and a well-defined framework to hold each response contributed by each wiki editor --- just like SurveyMonkey. However, a wiki-survey has two important differences:

1. Transparent sharing of all wiki-survey responses is a given. There is no waiting for the survey administrator to publish anything, no option for the survey administrator to hold anything back.
   
2. The questions themselves can be added to and/or edited on the fly by wiki-survey respondents. This frees the survey administrator from having to ask just the right questions; if someone does not see the question they wanted to answer, they can add that question in a place where everyone can respond to it.

One of my favorite wiki-surveys is this one, which I have used to run a contest that recognizes the most popular student project of the semester. It is a simple and effective wiki-survey that leverages option #1 heavily and ignores option #2. I have previously posted two case studies about its use on these pages: "Pros and cons of male enhancement" and "Delete all your links, except to me." I have modified it for use in many client engagements as well, fully leveraging both options #1 and #2.

This fall I significantly upgraded my pseudo-survey technology by abandoning the wiki platform altogether. You can see my post-wiki pseudo-survey at http://webwhompers.net, where the blood from my students' recently fought competition is still fresh.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Wiki Whomping

"When have I seen wikis work the best?" Thanks to Noah Flower for posting his thoughtful response to my last post (about working wikily), and closing with that question.

By way of answering, I'd like to quote from the pre-eminent prophet of working wikily, Clay Shirky. In his award-winning essay "A group is its own worst enemy," Shirky states, "Prior to the Internet, the last technology that had any real effect on the way people sat down and talked together was the table."

You can click here to read my original argument that Shirky is crazy if he really believes that. Today, instead of arguing against Shirky, I'd like to use his quote to put Noah's question in clearer context:

"When have you seen tables work the best?"

If you find that question confusing, good. Tables are such a fantastic technology for collaboration, and so flexible in the ways we can use them, that asking for "best example of using a table" is more of a Rorschach test than a question. More specifically, it's a great question for a furniture salesman to ask, as the person answering will suddenly feel an urge to find some connection between tables and whatever "works the best."

Answering Noah more earnestly (sort of), I have seen wikis work very well when they are tightly controlled. For example, Claire Reinelt and I use a wiki to publish our favorite reading list about SNA and leadership networks for social change. Our reading list is a joint effort that neither of us could have assembled alone. The most important feature of the site, however, is that no one can edit the wiki but me and Claire.

I'll close today's post with this passage from Wikipedia. It's from an article on participation inequality, but it also works well as a manifesto for Wikipedia's own governance, which is much more tightly controlled than it used to be:

"A major reason why user-contributed content rarely turns into a true community is that ... a few users contribute the overwhelming majority of the content, while most users either post very rarely or not at all. Unfortunately, those people who have nothing better to do than post on the Internet all day long are rarely the ones who have the most insights. In other words, it is inherent in the nature of the Internet that any unedited stream of user-contributed content will be dominated by uninteresting material."

Next time we'll answer the question, "When have I seen social bookmarking work the best?"

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Working Wikily

Last month the Monitor Institute launched a blog http://workingwikily.net about how the social sector is adopting the new tools, strategies, and practices of networking.

They explain here that "Working Wikily" was coined "to describe the new ways that people are applying network theory and networked technology to do the work they’ve always done in a more collaborative form and also to begin working in new ways altogether."

As my contribution to "Working Wikily," I'd like to offer a reality check on what happens when people use a wiki. Before I continue, however, let me make clear that (1) collaboration is great, (2) wikis are great, and (3) the reality check I am about to deliver is aimed at people who associate "collaboration" with "wiki" and thereby set themselves up for disappointment when they learn this the hard way:

Jakob Nielsen summarizes Web collaboration in general with the 90-9-1 rule as pictured below.
90% do nothing, 9% do a little, and 1% do practically everything.

Blogs are even more skewed than average Web sites, with 95% doing nothing, 4.9% doing a little, and 0.1% doing practically everything.

Wikis are the most skewed of all.

Most community facilitators I know who have set up wikis lament that they can't get anyone else to edit it without resorting to bribery. That is 100% doing nothing while one outsider does everything.

With a hugely successful wiki like Wikipedia, the ratio is slightly better, 99.8% percent do nothing, 0.197% do very little, and 0.003% do practically everything.

The above dose of reality is called "participation inequality" by Nielsen. Let me reiterate that I do not see this inequality as a problem, even though Nielsen presents it that way (as would, I suspect, many who set out to "work wikily" and end up proving Nielsen's point).

Thank you to Laurie Damianos for alerting me to these statistics during her presentation on MITRE's use of social bookmarking on their corporate intranet. Her experience at MITRE was consistent with the general trends claimed by Nielsen. Unlike many others in her position, though, she did not get discouraged by low participation, nor did she try to change it. Instead, she did a great job explaining to the powers-that-be that MITRE's social bookmarking system was working great, even with most people contributing nothing.

So let's raise a toast to the 99.8% who have perfected the most popular way of "working wikily" -- those who do nothing and, when they feel like it, coast off the hard work of the 0.003% who give it all away.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Geographic networks

Geography (or spatial arrangement) of nodes is often an important factor in network dynamics. Though it is straightforward to map geographical information by itself, mapping that information simultaneously with network data is quite a challenge.

In collaboration with Holly Massett and her team at the National Cancer Institute, I have been tackling the geographic + network mapping problem head on. Holly and I recently presented some of our results, and she graciously gave me permission to share them.

What happens when we draw a network map with geographically located nodes? We get a map with lines on it:
The geography is plainly apparent, but the network structure is all but invisible. That's a shame, because the network structure hidden above is actually quite striking when you redraw the above network using traditional network layout techniques:
Now we can clearly see that there is one node that bridges between two distinct clusters.

As a simple first step toward integrating these two important views of the above collaboration network, I created this slide show, which morphs back and forth between pure geography and pure network information, showing the interaction of the two along the way (RSS readers must view my actual blog to see this):


This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Working the math in your favor

Last week I was part of a panel discussion about technology and business. Forty or fifty accomplished businesswomen attended--I was the only man in the room. In hindsight, this was a perfect opportunity for me to focus on Bion's three pillars of group behavior (or at least the first of those three pillars, having the mating partner ratio so heavily in my favor); however, I confess I occasionally let my thoughts drift from that #1 priority and instead contemplated the diverse perspectives on technology represented in in the room.

The audience was predominantly business-savvy and ranged from the tech-curious to the tech-confused. It was not the most receptive setting for preaching a Taoist bliss of ignorance, but that's what I pitched, with lines like "the best technology is whatever you're using now"; "reading email when you receive it lowers your IQ more than chronic pot-smoking"; and "technology is implemented to benefit its creators, not its users, so look for technology where the users and the creators are the same."

The room was filled with questions about LinkedIn and Twitter. I realized that LinkedIn has taken hold of a much wider business audience than it had when I last disparaged it on these pages 2-3 years ago. Sensible successful business people speak with complete earnestness about the 500,000 people in their LinkedIn network, and I am speechless.

I have some hope. My LinkedIn network has 2,850,200 people, including 16,927 new connections in just the last 4 days. Before I leverage all of them, however, I sense that LinkedIn is giving me an opportunity to update this old joke:

A museum guide leads a group of tourists through a dinosaur exhibit. Stopping at an impressively scary skeleton baring its fossilized teeth, he says, "This T-Rex is 70 million and 3 years old." One of the tourists responds, "Wow! How do they figure that out so precisely?" The guide responds, "Well, when I started working here, this skeleton was 70 million years old, and that was 3 years ago."

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Viewing network data in Excel... with banana

Today I received an invitation from Harvard's Program on Networked Governance to watch Marc Smith demonstrate the powers of .NetMap --- a network visualization tool that runs inside Excel 2007. Maybe I will upgrade my MS Office and check it out; the screen shots look good.

On a more personal note, my BU faculty site is up. The site demonstrates what any monkey can do after enough time hanging with my students.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Structural equivalence: related tags in social bookmarking

In my "Holy Trinity of Network Power," structural equivalence is conceptually the most obscure. But practically speaking, it is easy to use. For example, searching for "sna" with the social bookmarking engine delicious provides the following:

I have enlarged and highlighted the "Related Tags" provided by delicious. This sort of information helps people find and learn from others with shared interests, using structural equivalence, regardless of how many degrees of separation they have on Facebook or LinkedIn. I'll expand more on this idea soon.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Structural equivalence: social bookmarking on a corporate intranet

Last week Laurie Damianos of MITRE presented to the Boston KM Forum, sharing her experience implementing a social bookmarking system within the enterprise.

For newbies, I often describe social bookmarking as similar to Amazon.com in its ability to track both people who read the same "books" and "books" that share common audiences--whether those "books" are literal or metaphorical. For the mathematically curious, structural equivalence is the underlying principle. Also, here's an introduction to social bookmarking I wrote a while back. Bill Ives has written a few times about applying social bookmarking within the enterprise, including specific references to MITRE's and IBM's experiences.

Laurie's presentation was great and left me feeling more excited than ever about business applications of social bookmarking. But I also left feeling puzzled by the response I got to one of my (many) questions. One way MITRE manages its in-house social bookmark system is by deleting bookmarks created by people who have since left the company. When I asked if there had been any debate within MITRE about deleting this information, I got two responses from the group: (1) Bookmarks are deleted, but the content (referenced by the former bookmarks) remains; and (2) Without the context of an owner, what good is a bookmark?

These two assertions strike me as odd, especially coming from a group that aims to solve the "lost knowledge" problem (e.g., Dave DeLong).

Deleting bookmarks of ex-employees seems to me on a par with burning bibliographies of articles whose authors are dead. After all, the artices and their references still exist. Furthermore, the authors are no longer around to provide context to their bibliographies. So why don't we save library shelf space and rip out all those bibliographies? Anyone who has ever done research can answer that question.

If bibliography-burning seems extreme, here's a milder example much closer to the MITRE reality: Amazon.com could save tons of disk space if it deleted the purchase records of people who haven't bought anything for the past year (i.e., those who have "left Amazon"). I wonder what the managers of Amazon would say to someone who suggested this strategy and argued that (1) the products purchased are still listed, and (2) the purchasers have left, so why bother to keep those records?

As pioneers of collaborative filering, managers at Amazon would probably recognize purchase records of the departed as a valuable resource. Acquiring those records in the first place is one of the biggest competitive advantages a service like Amazon can achieve--commonly known as surmounting the "cold start problem."

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Rob Cross Braintrust Keynote and Density

As an example of network-cluster-driven-behavior, last time I suggested a simple way to stereotype the work of Rob Cross. The first row of the table below, from his "Braintrust Keynote" presentation, was my Exhibit A:
The other rows of the above table deserve comment as well. Let's focus today on the third row, Centrality, with apologies to those who thought that my recent series on network centrality was finished.

In all my posts on centrality, I never actually described a mathematical formula for calculating it. There are quite a few reasonable ways to define centrality. See this post for links to a few of them. We see above that Cross's Braintrust Keynote describes centrality as the "average # of relationships per person." Unfortunately, this notion of centrality has nothing at all to do with what other people mean when they say "centrality."

First, a preliminary clarification: "Centrality" is most commonly used to describe a single node in a network, but it is also used to describe a global property of an entire network (much like "centralization" in the bottom row of the Braintrust Keynote table above). So we should be clear that "average # of relationships per person" is a global property of an entire network.

With that in mind, observe the following two networks that have exactly the same number of nodes, exactly the same number of edges, and hence exactly the same value of "centrality" or "average # of relationships per person":
I don't think too many people would describe the above two networks as having equal centrality, despite the Braintrust Keynote assertion.

It's a shame to equate "centrality" and "average # of relationships per person." They are two of my most favorite network metrics. I have devoted enough recent bandwidth to centrality to make clear my affinity for that metric. Soon, I will explain why I like "average # of relationships per person" as an alternative to density (top row of the Braintrust Keynote table) that is much less susceptible to the network size bias noted by Kathleen Carley.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Clustering: Guide to Stereotyping Rob Cross and Kathleen Carley

Recently I mentioned how network clustering on the WWW indicates that Rob Cross and Kathleen Carley each have their own close-knit camps that co-dominate the world of "organizational network analysis." Before that, I shared Ron Burt's point that such close-knit camps are known not only for amazing productivity but also for stereotyping outsiders.

I am outside both the Cross and Carley camps, but I enjoy stereotyping as much as anyone, so today I provide convenient superficial labels with which my readers can simplify the contributions of these two notable network leaders.

Guide to stereotyping Rob Cross and Kathleen Carley:

1. Rob Cross provides stories for business
2. Kathleen Carley provides computer models for the military

Wasn't that easy? Now let's look at one example of each stereotype.

(1) The recent research of the Network Roundtable features Cross's "Braintrust Keynote Presentation." Here is his third slide:
Note the simple and compelling story in the top row of the table: Network density within and across departments of less than 20% indicates little collaboration. If you read the actual presentation, you'll see that the "target density" is only 9.4% because the current density is less than half that, so the target is a healthy step up towards 20%. I will skip the other rows of the table for now.

(2) Kathleen Carley's camp responds to the above story with the following article:
As far as stories go, this article sucks. But look, it is classified under "statistical simulation," because the researchers use computer programs not only to analyze networks, but also to create the very networks that they study (no pesky data collection necessary).

For those whose eyes are glazing over, let me summarize the computer model punchline with a picture. The following three networks all have exactly the same density, 20%; and so according to Cross each of the three networks below has exactly the minimum recommended allowance of connectivity to indicate collaboration:
As you can see, density of 20% means different things depending on how many nodes are in the network.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Read email or smoke pot---The choice is yours

While playing hooky from Rob Cross's school of networks, I am free to indulge in all kinds of reckless neuron-destroying behavior. One option is attending to email, which is even better than pot-smoking at reducing IQ.

Chances are you know someone with an email problem. Give them the gift of 5 additional IQ points by inviting them to take this survey, created by Peggy Kuo at the University of New South Wales, Australia:

Email Addiction in the Workplace. Link to survey: http://www.questionpro.com/akira/TakeSurvey?id=1023102

The aim of this study is to determine if Email Addiction exists in the workplace; if so what factors contribute to it and how can it be measured or determined. In addition we also aim to determine the impacts it has on productivity in the workplace.

If you decide to participate, you will be asked to complete an online survey. It is envisaged that the survey will take between 5-10 minutes to complete. There are no known or foreseeable risks associated with the survey.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Clustering: Rob Cross and Kathleen Carley

Next Monday, Sept 8, begins the 2-day Network Roundtable Fall Conference. Rob Cross at UVA has led the Network Roundtable from its inception. He and his colleagues have quite an agenda planned for their time in DC.

My regular readers with sharp eyes may have noticed Rob Cross in a recent post of mine. That post introduced network clustering with an example --- a WWW clustering analysis of "organizational network analysis" computed by Grokker:

One of my favorite metaphors for clustering analysis is the table of contents. It is useful for seeing the big picture, all-inclusively, broken down into sub-categories. In an organizational network setting, a natural application would be identifying communities of practice (including those that don't yet recognize themselves as such).

Continuing with the book metaphor, we can see that the WWW authors of organizational network analysis have devoted "chapters" to these topics:

1. Social networks
2. Organizational systems
3. Public health
4. Information management
5. Knowledge
6. Tools
7. Rob Cross
8. Kathleen M Carley
9. Other

Most of these "chapters" are based on fields or methods of work. Two "chapters" stand out for being based on individual people.

Another way to view these "book chapters" is as "closed networks" (relatively speaking), as I described in my last post. I refer my readers again to that post, this time keeping Rob Cross and Kathleen Carley in mind. It's fun to speculate how the Cross and Carley camps employ stereotypes to describe their counterparts.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Network Clustering: The Power of Reputation

As we leave our series on network centrality and begin an exploration of network clustering, who better to help us bridge the gap than Ron Burt. Burt is perhaps best known for his amazing network-based research on innovation and the source of good ideas, which brought "structural holes" to the world's attention. In Brokerage & Closure he expands these ideas into book form and brings additional attention to "closure," a key trait related to network clustering.

Very briefly, closure refers to the interconnectedness of one's contacts: When my contacts don't know each other, my network is "open," and when they do know each other, my network is "closed." Assuming that I am #1 (naturally), two extremes of open (left) and closed (right) are pictured below:"Open" and "closed" are pretty much the same as bridging and bonding, as I have discussed before:


For more discussion of network closure, I recommend Burt's online notes for his executive MBA course, "Strategic Leadership," specifically the chapter on Closure, which I would sum up with these two points:

1. The peer pressure created by closed networks builds commitment and productivity
   
2. The peer pressure created by closed networks reinforces groupthink and promotes mindless stereotypes
   

Click on the image below and you can read what Burt himself says:

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

NSF and Google-induced stupidity

The NSF has just published Fostering Learning in the Networked World: The Cyberlearning Opportunity and Challenge. Reading it reminds me of why I bailed out of academia. The introduction starts: "To address the global problems of war and peace, economics, poverty, health, and the environment, we need a world citizenry with ready access to knowledge about science, technology, engineering, and mathematics."

Wow. Another thing the world citizenry needs is a ban on vapid topic sentences whose only purpose is to inflate the perceived importance of the author's pet project.

In the NSF-funded land of cyberlearning, there is a five-tiered hierarchy of human interaction, represented by the cool picture below: The report explains the picture thus: "[The figure above] depicts historical advances in the communication and information resources available for human interaction. Basic face-to-face interaction at the bottom level requires no resources to mediate communication. The second wave of resources offered symbol systems such as written language, graphics, and mathematics but introduced a mediating layer between people. The communication revolution of radio, telephony, television, and satellites was the third wave. The outcomes of the fourth wave—networked personal computers, web publishing, and global search—set the stage for the fifth wave of cyberinfrastructure and participatory technologies that are reviewed in our report."

So, we are going to solve the "global problems of war and peace" with a framework that explicitly omits mediation from the realm of face-to-face communication. I wonder how much cyberinfrastructure South Ossetia would need to put this framework to use.

Next time I will get back on my network clustering thread again...

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Clustering: The Un-Google

Having finished our series on network centrality, we now approach its most natural complement: network clustering.

An easy way to appreciate the usefulness of network clustering is to try search engines that (unlike Google) are not centrality-driven. There are quite a few such search engines out there. They are great at providing a sense of direction within a previously unknown field --- when you're not yet sure exactly what question you're asking. In contrast, Google is better when your query is more specific, or when you just don't care about the rest of the forest, dammit, and want to find the biggest most popular tree ASAP.

Below are two examples of how non-centrality-based search engines display the WWW of "organizational network analysis". Click on either image to go to the search engine pictured.



There are dozens more search engines listed here by search engine junkie Bill Sebald.

I hope you enjoy the Un-Google world. Soon I'll say more about understanding this world with the help of network clustering.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

NetDraw / UCINET tutorial; networks = organizing

Link of the week: Network Mapping as a Diagnostic Tool, by Louise Clark. This is the best NetDraw user's guide I have seen. Thanks to Cai Kjaer at www.onasurveys.com (via his helpful wiki) for alerting me to this resource.

---

A few weeks ago I got an anonymous email with nothing but this quote:

"Science is organized knowledge. Wisdom is organized life."

--Immanuel Kant

That is some interesting spam. It got me thinking: Is "organized" really the fundamental property of science and wisdom? No, I decided; it's just a word making a pithy quote. I then forgot the matter, only to remember it today, when I read "Using Emergence to Take Social Innovation to Scale," by Meg Wheatley and Debbie Frieze of The Berkana Institute. They say:

"Networks are the only form of organization on this planet used by living systems."

True enough, but I claim their statement is too weak. I would rephrase it "Networks = Organization." If you disagree, please send me a counterexample in the form of an organizing principle that does not invoke things (i.e., nodes) and relationships (i.e., links). And feel free to consider other planets, non-living systems, dark matter, alternate universes, etc. You must also agree to let me use confusing mathematical machinery in order to refute your counterexample. The best "counterexamples" I have so far are organizing by space and time. For example, jellyfish organize by drifting near the surface of the ocean, and people organize by sleeping when it's dark.

Once you accept that Networks = Organization, Wheatley and Frieze's assertion becomes somewhat less interesting; however, it does (somehow) lead to the Berkana-esque question: Isn't it odd that the words "organization" and "organic" have the same root? Doubters like myself can verify right here the etymological network connecting "organization" with "organic." The root is the Greek organon, literally "that with which one works," and which since the 12th century has described not only tools but also musical instruments and body parts.

Putting all our quotes and equations together, we have:

"Science is knowing tools, musical instruments, and body parts. Wisdom is living tools, musical instruments, and body parts."

And that, dear reader, is an org chart that really counts.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Pros and Cons of Male Enhancement

Just in time for my last installment on network centrality, I have learned that Google now ranks Connectedness the #1 site on the Web for "pros and cons of male enhancement." It's tempting to take credit and say that this honor was the result of long, hard work on my part; but it was endowed upon me more by the fates of centrality than by anything I did. (Those who doubt my boast and are not afraid to look, click here: http://www.google.com/search?q=pros+and+cons+of+male+enhancement.)

Without taking anything away from the experts who have filled my blog with their thoughts on the topic, I now want to make perfectly clear my position on male enhancement: The field of collective leadership needs it bad, especially the non-profit/social-change sector.

I love working with collective leadership programs, and I am fortunate to do so regularly. The recipe for this work adapts to the participants, but it almost always involves something like the picture at right. See W.K. Kellogg Foundation's Collective Leadership Framework and the D.C. Leadership Learning Community's Nature of Collective Leadership for more.

In other sectors, collective leadership draws less with crayons and uses other more dangerous sticks. Speaking of collective leadership in the field of science, John Ziman says that each individual's contribution is "merely a tiny tentative step forward, through the jungles of ignorance." I don't think his savage choice of setting --- where only the fittest survive, thanks to teeth, claws, and other weapons --- was any accident.

My Introduction to Web Programming class has filled up again for this fall. It's my personal collective leadership learning lab. How can I equip 75 computer-illiterate college kids with the wherewithal to make their own websites (like these)? I can't. But together, they can. I facilitate my students' learning by dropping them into the Internet jungle and encouraging them to trust their own most primitive hacking instincts.

In the spirit of crayons and group hugs, my first gift to my students each term is an online discussion forum where they are encouraged to share anything relevant to the class. Speaking to a ballroom-full of faculty about his experience, Will Mundel noted first and foremost that "Thanks to the online forum we used in CS-103, students stop being individuals in a class. Rather, they are all in it together."

I am honored by Will's comment, but that's not the whole story of how my students learn to build their own websites. Underlying the experience of the class is a curriculum I have modeled on the traditional male rite of passage: (1) Throw a boy out of society into the wilderness; (2) Let him suffer and learn; and (3) Welcome the transformed man back into society. (That's my paraphrasing. Here's what the American Psychological Association says about this method of transformational learning.) If you look closely at this gallery of student projects, you'll see a quote from another student that speaks directly to her painful but ultimately victorious journey alone through the wilderness.

After subjecting my students to this webified passage of suffering, I top it off with a month-long tournament of hand-to-hand combat. Within the cage of this special-built wiki, the students compete for Google-rank supremacy. This part of the class evolved from my desire to translate the inner workings of the Google centrality algorithm into the real-life experience of the kids.

Inviting students into this kind of centrality-based competition is not easy. My first attempt provoked class revolt because students perceived the rankings as an unfair system of grading their work. (The fact that the competition had no impact on actual grades was irrelevant to this revolt.) My second attempt went smoothly: I was careful to provide a fair system for peer reviews in parallel with the same centrality-based competition. With fair peer reviews in hand, the students no longer were bothered by the arbitrariness of centrality rankings.

Last spring was my third and by far most successful use of the centrality competition. Not only was there no resentment at the arbitrariness of centrality rankings, but there was a positive embracing of the system. Students discovered how to form alliances and deliberately manipulate the Google algorithm into boosting their own rankings. A flurry of new links and surprise defections preceded the day of our awards ceremony. Three alliances shared top honors. When I refused to award a prize to one of the alliances because their team leader had skipped class that day, his teammates/co-conspirators texted him and made him show up, 20 minutes late, so that they could receive their prize: a one-half of one percent boost in final course grade.

Technical postscript: For those wondering how it's possible to share top honors in a Google centrality competition, the answer is quite technical. From this more-or-less readable description of the Google algorithm, you can discover a "damping factor" that Google does not allow users to see or edit. I provide my students with a Google centrality calculator that allows them to edit this damping factor to whatever they want. Changing the damping factor can sometimes change the winner of the rankings; I award first prize to anyone who can find a damping factor value that puts them atop the rankings. In the following network, every single node with a label can win the Google centrality contest with the right damping factor:

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Making us Lazy Conformists, Says NSF

[Ed note: This is the last tangent before we really finally close the network centrality thread with a positive note, coming soon.]

The NSF reports today: "The Internet gives scientists and researchers instant access to an astonishing number of academic journals. So what is the impact of having such a wealth of information at their fingertips? The answer, according to new research released today in the journal Science, is surprising--scholars are actually citing fewer papers in their own work, and the papers they do cite tend to be more recent publications. This trend may be limiting the creation of new ideas and theories."

This is an argument for Google-induced stupidity that I can agree with (unlike last week's).

My only beef with the NSF blurb is the notion that anything "surprising" is happening here. There is plenty of evidence of our lemming-like ways in other contexts; we should expect a human tendency to dive over the cliff of the web's dark side. Here's a first-person demonstration. By doing a bit of Googling I can share the first decent link that pops up to support the claim that humans are lemmings: Conversation, Information, and Herd Behavior, in the American Economic Review, 1995. Using Google in this way, I can feel myself regressing into a rodent even now.

One of the first, most famous and shocking demonstrations of human lemmingness was devised by Solomon Asch in the 1950's. Most people after reading this story find it hard to believe that it could happen to them. I had the "good fortune" to be tricked by my college psychology professor into Asch's trap, exposing my irrational lemmingness for all my 200 classmates to see. I have no doubt that I am a weak-willed conformist.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Network Centrality: Making Us Stupid, Says Atlantic Monthly

"Is Google Making Us Stupid?" asks Nicholas Carr on the cover of this month's Atlantic Monthly. In a nutshell, Carr laments the decline of "deep reading" and suspects that we are losing "deep thinking" as well. I would not argue the "deep reading" point, but the connection to "deep thinking" is debatable and surely this excellent rebuttal is not the last blog post that will take Carr to task.

Here I will argue Carr on a different point. About two-thirds into his essay, he says:

"Sergey Brin and Larry Page, the men who founded Google, speak frequently of their desire to turn their search engine into an artificial intelligence. 'The ultimate search engine is something as smart as people—or smarter,' Page said in a speech a few years back. 'For us, working on search is a way to work on artificial intelligence.' In a 2004 interview with Newsweek, Brin said, 'Certainly if you had all the world’s information directly attached to your brain, or an artificial brain that was smarter than your brain, you’d be better off.' ....

[Carr continues] "Such an ambition is a natural one, even an admirable one, for a pair of math whizzes with vast quantities of cash at their disposal and a small army of computer scientists in their employ.... Still, their easy assumption that we’d all 'be better off' if our brains were supplemented, or even replaced, by an artificial intelligence is unsettling. It suggests a belief that intelligence is the output of a mechanical process, a series of discrete steps that can be isolated, measured, and optimized."

Two counterarguments immediately come to mind in response to the above:

1. For many of us, it is quite natural to believe that intelligence can be the output of a mechanical process. I suspect I am in a minority on this point, so for those who are curious to consider intelligence outside the stuff of brains, I simply recommend the book, The Mind's Eye, a collection of essays around this topic edited by Douglas Hofstadter and Daniel Dennett.
2. In the passage above, there is a belief espoused explicitly by Brin and implicitly by Carr that is even more unsettling (at least to me) than the notion of mechanized intelligence: That we'd be "better off" if we were smarter. Read Carr's entire essay and you'll see that, just like his essay title suggests, he is very pro-smart and anti-dumb. I'll grant that with more intelligence, we have a way to boast of being "better than..."; but being "better off" is another question altogether.
   

In short, Carr's passion for intelligence combined with his strict accounting of its boundaries are a recipe for fundamentalism.

...

My regular readers may be wondering what happened to the "celebration of competitiveness" that I promised last time. Or maybe, what does any of this have to do with networks? Good questions. I beg your patience, dear reader-- I just could not resist this tangent, and I promise to celebrate centrality, measurement, and competitiveness soon. Meanwhile, I close with this chapter from the Tao Te Ching, which comments on the consequences of increasing intelligence:

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: More Current Events

Last week we kicked off our "Separation of Network Power" series in honor of the June 12 Supreme Court ruling on hearings for Guantanamo Bay detainees.

This week we'll continue the series, inspired by Congressional action of June 19 to let the White House and phone companies off the hook for warrantless tapping of domestic US communications since 2001.

Showing how far one branch of government can implicitly subjugate itself to another, Congressional Democrats claimed victory for including a special clause in the law that prohibits the White House from breaking it. In the words of the NY Times:

The most important [White House] concession that Democratic leaders claimed was an affirmation that the intelligence restrictions were the “exclusive” means for the executive branch to conduct wiretapping operations in terrorism and espionage cases. Speaker Nancy Pelosi had insisted on that element, and Democratic staff members asserted that the language would prevent Mr. Bush, or any future president, from circumventing the law. The proposal asserts “that the law is the exclusive authority and not the whim of the president of the United States,” Ms. Pelosi said.

In the wiretapping program approved by Mr. Bush after the Sept. 11 attacks, the White House asserted that the president had the constitutional authority to act outside the courts in allowing the National Security Agency to focus on the international communications of Americans with suspected ties to terrorists and that Congress had implicitly authorized that power when it voted to use military force against Al Qaeda.

Network centrality and the executive branch make for tough competitors in the struggle not only to separate but also to balance the powers of the collective. Last time I lamented the dark side of centrality and competition. Next time I'll celebrate the good side.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: Size Does Matter

Today, the summer solstice, ranks with sunrises and full moons as one of the original inspirations to human time-telling and measurement. Here is a a classic New Yorker cartoon showing what that moment might have looked like.

We have come a long way since then. As recounted by author Dava Sobel, our ability to measure time with precision turned out to be the final critical breakthrough that enabled us to navigate across oceans, rather than simply drift and hope for a safe harbor to appear on the horizon. As the cartoon attests, however, we paid a high psychological price for this ticket to global connectedness. We measure time not just to travel over the horizon but also to worry about getting there soon enough.

So it is with network centrality. No matter what kind of network centrality catches your fancy, it can both empower you to navigate farther and more accurately across great "distances," and it can nag you with the question of how well you measure up.

One big difference between time and centrality is that unlike time, which rests on rhythms of nature (earth, moon, sun, cesium atoms, etc), centrality is a mathematical abstraction with a maddeningly circular non-grounding in reality. In other words, when it comes to centrality, "perception is reality." Martin Kilduff and David Krackhardt argue this much more rigorously in their Analysis of the Internal Market for Reputation in Organizations, which states: "We found that being perceived to have a prominent friend boosted reputation, but that actually having such a friend had no effect." The implications of this result for the practice of ONA consulting could not be more profound.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.

Network Centrality: All Your Links Are Belong to Us

Yesterday was a full moon. Tomorrow is the longest day of the year. What better day to celebrate the brightest metric known to network science: centrality.

Connectedness celebrates centrality by putting Google, the world's most popular centrality-based tool, to work. For any set of keywords you can imagine, Google points you to the center of that universe. Each link below does exactly that, using the highlighted text as the keywords. Results are real-time and may change after this post goes to press.

• Network Centrality: The center of this universe is Steve Borgatti. Yeah!
• Organizational Network: The center of this universe is Valdis Krebs. Kudos to you, Valdis. I am jealous.
• Community Network: Apparently centered in Seattle. Interesting. How did Seattle beat out Portland, OR?
• Collaboration, Innovation: Centered on Dave Pollard. This confirms my excellent impression of him from a couple months ago--which was the first I heard of him.
• Leadership, and most other words you care to look up: Wikipedia has the first answer you will find.

No celebration of centrality would be complete without asking, "What universe am I the center of?" For Connectedness, the answer is: sears refrigerator customer service repairman. To all my readers, let me say: Welcome to the inner sanctum.

While you're celebrating having "arrived," let me add that this weekend is the fourth birthday of Connectedness. All the more reason for jubilation.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2007 by Connective Associates LLC except where otherwise noted.

Holy Trinity of Network Power

Last Thursday the US Supreme Court ruled that prisoners at Guantanamo Bay have a right to hear and to challenge the reasons for their detention.

Eric M. Freedman, a habeas corpus expert at Hofstra University Law School, called the decision "a structural reaffirmation of what the rule of law means," and said it was as important a ruling on the separation of powers as the Supreme Court has ever issued, according to the NY Times.

Dating back at least to ancient Greeks, the separation of powers traditionally splits state power into three parts: executive, legislative, and judicial.

Over the next few posts, Connectedness will celebrate the separation of powers by comparing each of its three components to three notable pillars of the network perspective: centrality, clustering, and structural equivalence.

Stay tuned for something like this:

Politics	Networks	Easy-to-Remember Stereotype
Executive	Centrality	Tyrannical Dictator
Legislative	Clustering	Mob of Special Interests
Judicial	Structural Equivalence	Politically Unaccountable Intelligentsia

Hopefully by July 4th, we'll have celebrated all three.

This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License and is copyrighted (c) 2008 by Connective Associates LLC except where otherwise noted.